Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations6057
Missing cells0
Missing cells (%)0.0%
Duplicate rows154
Duplicate rows (%)2.5%
Total size in memory520.5 KiB
Average record size in memory88.0 B

Variable types

Numeric10

Alerts

Dataset has 154 (2.5%) duplicate rowsDuplicates
USD-AUD is highly overall correlated with USD-CAD and 5 other fieldsHigh correlation
USD-CAD is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-CHF is highly overall correlated with USD-CNY and 1 other fieldsHigh correlation
USD-CNY is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-EUR is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-GBP is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-JPY is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-NZD is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-XAU is highly overall correlated with USD-CHF and 2 other fieldsHigh correlation

Reproduction

Analysis started2025-04-21 23:56:04.176076
Analysis finished2025-04-21 23:56:19.718012
Duration15.54 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

USD-AUD
Real number (ℝ)

High correlation 

Distinct266
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3153998
Minimum0.90966979
Maximum1.9696671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:20.076236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.90966979
5-th percentile0.96328014
Q11.1427265
median1.3229263
Q31.4316392
95-th percentile1.6335213
Maximum1.9696671
Range1.0599973
Interquartile range (IQR)0.28891268

Descriptive statistics

Standard deviation0.20773304
Coefficient of variation (CV)0.15792388
Kurtosis-0.022544503
Mean1.3153998
Median Absolute Deviation (MAD)0.13799407
Skewness0.15130451
Sum7967.3768
Variance0.043153016
MonotonicityNot monotonic
2025-04-21T19:56:20.316760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.423082396 45
 
0.7%
1.448645516 44
 
0.7%
1.842978253 44
 
0.7%
1.336541032 44
 
0.7%
1.321702353 43
 
0.7%
1.376841526 43
 
0.7%
1.535626536 43
 
0.7%
1.446549978 43
 
0.7%
1.305994515 43
 
0.7%
1.361655773 43
 
0.7%
Other values (256) 5622
92.8%
ValueCountFrequency (%)
0.9096697899 21
0.3%
0.9114939386 21
0.3%
0.9317927693 21
0.3%
0.9326618168 22
0.4%
0.9339684319 23
0.4%
0.9370314843 22
0.4%
0.9415309293 22
0.4%
0.9496676163 21
0.3%
0.9521089213 22
0.4%
0.9588647042 21
0.3%
ValueCountFrequency (%)
1.969667126 1
 
< 0.1%
1.930129319 20
0.3%
1.876876877 21
0.3%
1.857700167 22
0.4%
1.842978253 44
0.7%
1.816530427 22
0.4%
1.802776275 23
0.4%
1.782531194 21
0.3%
1.780626781 22
0.4%
1.774937877 20
0.3%

USD-CAD
Real number (ℝ)

High correlation 

Distinct267
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2268041
Minimum0.9431
Maximum1.6016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:20.542294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.9431
5-th percentile0.9923
Q11.0776
median1.2613
Q31.3328
95-th percentile1.45674
Maximum1.6016
Range0.6585
Interquartile range (IQR)0.2552

Descriptive statistics

Standard deviation0.15347267
Coefficient of variation (CV)0.12509958
Kurtosis-0.70642264
Mean1.2268041
Median Absolute Deviation (MAD)0.099
Skewness0.0019533556
Sum7430.7522
Variance0.02355386
MonotonicityNot monotonic
2025-04-21T19:56:20.732654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2398 63
 
1.0%
1.3516 46
 
0.8%
1.3093 45
 
0.7%
1.3412 45
 
0.7%
0.9987 44
 
0.7%
1.3127 44
 
0.7%
1.1657 43
 
0.7%
1.0174 43
 
0.7%
1.303 43
 
0.7%
1.354 42
 
0.7%
Other values (257) 5599
92.4%
ValueCountFrequency (%)
0.9431 23
0.4%
0.9451 21
0.3%
0.9552 21
0.3%
0.9634 22
0.4%
0.9685 22
0.4%
0.9706 23
0.4%
0.9716 20
0.3%
0.9777 23
0.4%
0.9837 20
0.3%
0.9863 23
0.4%
ValueCountFrequency (%)
1.6016 20
0.3%
1.5949 21
0.3%
1.5891 1
 
< 0.1%
1.5868 21
0.3%
1.5842 23
0.4%
1.5718 22
0.4%
1.5677 22
0.4%
1.5653 21
0.3%
1.5585 22
0.4%
1.5584 23
0.4%

USD-CHF
Real number (ℝ)

High correlation 

Distinct273
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0457281
Minimum0.7855
Maximum1.7193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:20.915987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.7855
5-th percentile0.878
Q10.9209
median0.9825
Q31.1581
95-th percentile1.3639
Maximum1.7193
Range0.9338
Interquartile range (IQR)0.2372

Descriptive statistics

Standard deviation0.16940047
Coefficient of variation (CV)0.16199284
Kurtosis1.2887274
Mean1.0457281
Median Absolute Deviation (MAD)0.0718
Skewness1.2958135
Sum6333.9751
Variance0.028696518
MonotonicityNot monotonic
2025-04-21T19:56:21.112569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9551 67
 
1.1%
0.9129 46
 
0.8%
0.9202 44
 
0.7%
0.9153 44
 
0.7%
1.0412 43
 
0.7%
0.9653 42
 
0.7%
0.9352 23
 
0.4%
0.9262 23
 
0.4%
0.91 23
 
0.4%
0.9315 23
 
0.4%
Other values (263) 5679
93.8%
ValueCountFrequency (%)
0.7855 21
0.3%
0.806 23
0.4%
0.8169 14
0.2%
0.8404 22
0.4%
0.8414 21
0.3%
0.8456 21
0.3%
0.8496 22
0.4%
0.854 22
0.4%
0.8614 23
0.4%
0.8641 23
0.4%
ValueCountFrequency (%)
1.7193 1
 
< 0.1%
1.6966 20
0.3%
1.6813 21
0.3%
1.6175 22
0.4%
1.5678 23
0.4%
1.4988 22
0.4%
1.4852 23
0.4%
1.4832 21
0.3%
1.481 20
0.3%
1.4767 23
0.4%

USD-CNY
Real number (ℝ)

High correlation 

Distinct247
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0298799
Minimum6.054
Maximum8.2775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:21.279353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.054
5-th percentile6.1437
Q16.4607
median6.8388
Q37.3919
95-th percentile8.277
Maximum8.2775
Range2.2235
Interquartile range (IQR)0.9312

Descriptive statistics

Standard deviation0.70019165
Coefficient of variation (CV)0.099602221
Kurtosis-0.82814535
Mean7.0298799
Median Absolute Deviation (MAD)0.4332
Skewness0.65496035
Sum42579.983
Variance0.49026835
MonotonicityNot monotonic
2025-04-21T19:56:21.416064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.2765 152
 
2.5%
8.277 131
 
2.2%
8.2766 90
 
1.5%
8.2768 87
 
1.4%
8.2764 87
 
1.4%
8.2772 65
 
1.1%
8.2771 63
 
1.0%
6.3561 45
 
0.7%
8.2773 45
 
0.7%
8.2767 45
 
0.7%
Other values (237) 5247
86.6%
ValueCountFrequency (%)
6.054 22
0.4%
6.0598 23
0.4%
6.093 21
0.3%
6.0942 23
0.4%
6.1129 23
0.4%
6.1191 21
0.3%
6.12 22
0.4%
6.1302 23
0.4%
6.1339 23
0.4%
6.1394 22
0.4%
ValueCountFrequency (%)
8.2775 41
 
0.7%
8.2774 42
 
0.7%
8.2773 45
 
0.7%
8.2772 65
1.1%
8.2771 63
1.0%
8.277 131
2.2%
8.2769 43
 
0.7%
8.2768 87
1.4%
8.2767 45
 
0.7%
8.2766 90
1.5%

USD-EUR
Real number (ℝ)

High correlation 

Distinct274
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83429488
Minimum0.63339245
Maximum1.1636025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:21.631939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.63339245
5-th percentile0.68873764
Q10.75631523
median0.83388926
Q30.90587916
95-th percentile0.97847358
Maximum1.1636025
Range0.53021006
Interquartile range (IQR)0.14956392

Descriptive statistics

Standard deviation0.09405004
Coefficient of variation (CV)0.11272997
Kurtosis-0.012057867
Mean0.83429488
Median Absolute Deviation (MAD)0.073634109
Skewness0.24305068
Sum5053.3241
Variance0.0088454099
MonotonicityNot monotonic
2025-04-21T19:56:21.832664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.780457348 45
 
0.7%
0.8127438231 44
 
0.7%
0.9104151493 44
 
0.7%
0.7063144512 44
 
0.7%
0.8900756564 43
 
0.7%
0.9455370651 40
 
0.7%
0.9035872413 23
 
0.4%
0.8087343308 23
 
0.4%
0.8185985593 23
 
0.4%
0.6959426543 23
 
0.4%
Other values (264) 5705
94.2%
ValueCountFrequency (%)
0.63339245 21
0.3%
0.6347191368 21
0.3%
0.6401229036 22
0.4%
0.6409023906 23
0.4%
0.642921435 22
0.4%
0.6588049279 21
0.3%
0.6664445185 21
0.3%
0.6729022273 23
0.4%
0.6753562504 21
0.3%
0.6793939806 22
0.4%
ValueCountFrequency (%)
1.163602513 1
 
< 0.1%
1.150218542 20
0.3%
1.147183664 21
0.3%
1.11049417 22
0.4%
1.070434596 23
0.4%
1.022913257 23
0.4%
1.020199959 22
0.4%
1.018018935 22
0.4%
1.013581999 21
0.3%
1.011940903 21
0.3%

USD-GBP
Real number (ℝ)

High correlation 

Distinct3996
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66938756
Minimum0.47449585
Maximum0.93554121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:22.047651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.47449585
5-th percentile0.50757299
Q10.60328185
median0.65091453
Q30.76458445
95-th percentile0.81514208
Maximum0.93554121
Range0.46104536
Interquartile range (IQR)0.1613026

Descriptive statistics

Standard deviation0.098706886
Coefficient of variation (CV)0.1474585
Kurtosis-1.0658071
Mean0.66938756
Median Absolute Deviation (MAD)0.08774701
Skewness0.006836426
Sum4054.4804
Variance0.0097430493
MonotonicityNot monotonic
2025-04-21T19:56:22.260962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6366588145 7
 
0.1%
0.7762769756 7
 
0.1%
0.7725587145 6
 
0.1%
0.7540340823 6
 
0.1%
0.8036647111 6
 
0.1%
0.6416014372 6
 
0.1%
0.7952918721 6
 
0.1%
0.773993808 6
 
0.1%
0.6562541016 6
 
0.1%
0.7883326764 5
 
0.1%
Other values (3986) 5996
99.0%
ValueCountFrequency (%)
0.4744958482 1
< 0.1%
0.4753981459 1
< 0.1%
0.4784002296 1
< 0.1%
0.478629206 1
< 0.1%
0.4789960243 1
< 0.1%
0.4802381981 1
< 0.1%
0.4806305873 1
< 0.1%
0.480746118 1
< 0.1%
0.480815463 1
< 0.1%
0.4828352083 1
< 0.1%
ValueCountFrequency (%)
0.9355412106 1
< 0.1%
0.9317059536 1
< 0.1%
0.92089511 1
< 0.1%
0.9183579759 1
< 0.1%
0.9117432531 1
< 0.1%
0.9045680687 1
< 0.1%
0.9020386073 1
< 0.1%
0.9009009009 1
< 0.1%
0.8995232527 1
< 0.1%
0.8960573477 1
< 0.1%

USD-HKD
Real number (ℝ)

Distinct212
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7845724
Minimum7.7418
Maximum7.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:22.464429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7.7418
5-th percentile7.7502
Q17.756
median7.7779
Q37.8001
95-th percentile7.8468
Maximum7.85
Range0.1082
Interquartile range (IQR)0.0441

Descriptive statistics

Standard deviation0.030767184
Coefficient of variation (CV)0.0039523281
Kurtosis-0.71577024
Mean7.7845724
Median Absolute Deviation (MAD)0.0221
Skewness0.65332167
Sum47151.155
Variance0.00094661963
MonotonicityNot monotonic
2025-04-21T19:56:22.683405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.7503 132
 
2.2%
7.7501 112
 
1.8%
7.75 110
 
1.8%
7.7994 103
 
1.7%
7.7551 88
 
1.5%
7.7502 86
 
1.4%
7.8 67
 
1.1%
7.7998 66
 
1.1%
7.7531 65
 
1.1%
7.808 46
 
0.8%
Other values (202) 5182
85.6%
ValueCountFrequency (%)
7.7418 22
 
0.4%
7.75 110
1.8%
7.7501 112
1.8%
7.7502 86
1.4%
7.7503 132
2.2%
7.7504 43
 
0.7%
7.7505 44
 
0.7%
7.7506 22
 
0.4%
7.7507 44
 
0.7%
7.7508 21
 
0.3%
ValueCountFrequency (%)
7.85 42
0.7%
7.8499 20
0.3%
7.8498 45
0.7%
7.8497 21
0.3%
7.8496 20
0.3%
7.8494 20
0.3%
7.8493 23
0.4%
7.8491 45
0.7%
7.8488 22
0.4%
7.8483 21
0.3%

USD-JPY
Real number (ℝ)

High correlation 

Distinct275
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.01636
Minimum76.27
Maximum160.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:22.863721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum76.27
5-th percentile79.82
Q1102.44
median110.26
Q3119.06
95-th percentile148.842
Maximum160.88
Range84.61
Interquartile range (IQR)16.62

Descriptive statistics

Standard deviation17.879149
Coefficient of variation (CV)0.16104969
Kurtosis0.37840449
Mean111.01636
Median Absolute Deviation (MAD)8.36
Skewness0.41058902
Sum672426.07
Variance319.66398
MonotonicityNot monotonic
2025-04-21T19:56:23.013263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
149.98 44
 
0.7%
106.28 44
 
0.7%
111.39 43
 
0.7%
115.77 43
 
0.7%
112.69 42
 
0.7%
97.88 23
 
0.4%
112.64 23
 
0.4%
109.98 23
 
0.4%
93.47 23
 
0.4%
117.4 23
 
0.4%
Other values (265) 5726
94.5%
ValueCountFrequency (%)
76.27 22
0.4%
76.66 23
0.4%
76.76 21
0.3%
76.91 22
0.4%
77.06 22
0.4%
77.62 22
0.4%
77.96 20
0.3%
78.12 22
0.4%
78.17 21
0.3%
78.32 23
0.4%
ValueCountFrequency (%)
160.88 20
0.3%
157.8 22
0.4%
157.31 23
0.4%
157.2 22
0.4%
155.19 23
0.4%
152.03 23
0.4%
151.68 22
0.4%
151.35 21
0.3%
150.63 20
0.3%
149.98 44
0.7%

USD-NZD
Real number (ℝ)

High correlation 

Distinct270
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4827035
Minimum1.1372683
Maximum2.402691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:23.149348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.1372683
5-th percentile1.2048193
Q11.3577733
median1.4551804
Q31.5802781
95-th percentile1.8345258
Maximum2.402691
Range1.2654227
Interquartile range (IQR)0.22250488

Descriptive statistics

Standard deviation0.2083039
Coefficient of variation (CV)0.14048925
Kurtosis2.4631801
Mean1.4827035
Median Absolute Deviation (MAD)0.11962271
Skewness1.2281648
Sum8980.7348
Variance0.043390513
MonotonicityNot monotonic
2025-04-21T19:56:23.319281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.361841209 45
 
0.7%
1.460493647 44
 
0.7%
1.433897333 44
 
0.7%
1.425110446 44
 
0.7%
1.475361464 44
 
0.7%
1.483679525 44
 
0.7%
1.294163323 43
 
0.7%
1.375515818 43
 
0.7%
1.455180442 42
 
0.7%
1.511258879 42
 
0.7%
Other values (260) 5622
92.8%
ValueCountFrequency (%)
1.137268282 21
0.3%
1.141813199 21
0.3%
1.154334526 21
0.3%
1.160496693 22
0.4%
1.167815018 22
0.4%
1.170823089 23
0.4%
1.176470588 23
0.4%
1.176609013 22
0.4%
1.192037192 20
0.3%
1.192179304 23
0.4%
ValueCountFrequency (%)
2.402691014 1
 
< 0.1%
2.371354043 20
0.3%
2.270663034 21
0.3%
2.235636038 22
0.4%
2.150075253 23
0.4%
2.132650885 21
0.3%
2.131741633 22
0.4%
2.080732418 23
0.4%
2.058036633 23
0.4%
2.052966537 20
0.3%

USD-XAU
Real number (ℝ)

High correlation 

Distinct239
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0011099779
Minimum0.000301
Maximum0.00353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size94.6 KiB
2025-04-21T19:56:23.498835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.000301
5-th percentile0.000485
Q10.000599
median0.000788
Q30.001276
95-th percentile0.002854
Maximum0.00353
Range0.003229
Interquartile range (IQR)0.000677

Descriptive statistics

Standard deviation0.0007554347
Coefficient of variation (CV)0.68058537
Kurtosis0.97321312
Mean0.0011099779
Median Absolute Deviation (MAD)0.000225
Skewness1.4696096
Sum6.723136
Variance5.7068158 × 10-7
MonotonicityNot monotonic
2025-04-21T19:56:23.884901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.000755 68
 
1.1%
0.000757 68
 
1.1%
0.000565 66
 
1.1%
0.00229 65
 
1.1%
0.000788 64
 
1.1%
0.000823 45
 
0.7%
0.000584 45
 
0.7%
0.000548 45
 
0.7%
0.000852 45
 
0.7%
0.000764 45
 
0.7%
Other values (229) 5501
90.8%
ValueCountFrequency (%)
0.000301 14
0.2%
0.00032 21
0.3%
0.00035 20
0.3%
0.000357 23
0.4%
0.000364 23
0.4%
0.000378 21
0.3%
0.00038 21
0.3%
0.000381 22
0.4%
0.000399 22
0.4%
0.000409 23
0.4%
ValueCountFrequency (%)
0.00353 1
 
< 0.1%
0.00337 20
0.3%
0.0033 21
0.3%
0.00329 23
0.4%
0.00324 22
0.4%
0.00319 22
0.4%
0.00318 20
0.3%
0.00314 44
0.7%
0.00309 21
0.3%
0.00306 23
0.4%

Interactions

2025-04-21T19:56:17.830559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:04.425170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.181410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.530612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.820569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.199107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.558773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.328137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.694495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.164056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.028292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:04.624830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.350623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.662828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.957215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.325636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.731736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.465004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.800164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.315329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.144475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:04.784365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.485442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.777666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.141337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.472776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.907528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.638450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.944872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.469937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.321588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:04.956619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.620761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.937204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.243120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.626774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.028793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.762076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.082325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.613040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.472859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:05.098915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.761579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.091571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.427336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.744949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.164619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.891466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.199427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.739345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.594567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:05.273767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.904794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.200285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.567860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.912294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.295419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.985148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.348161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:16.927276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.726862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:05.388769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.004607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.322449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.674697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.010817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.477673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.109817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.530598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:17.073785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:18.909334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:05.556081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.144397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.446593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.770652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.161977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.616750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.216057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.689841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:17.267938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:19.076982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:05.722237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.288931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.553016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:09.888682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.282777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:12.806296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.392267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.853389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:17.482485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:19.191686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:06.018546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:07.424402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:08.648069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:10.038248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:11.433759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:13.195654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:14.539382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:15.971633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-21T19:56:17.637376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-21T19:56:24.051170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
USD-AUD1.0000.9130.1840.5520.8240.5270.3770.7020.926-0.004
USD-CAD0.9131.0000.1120.4670.8740.5840.3690.6760.802-0.033
USD-CHF0.1840.1121.0000.654-0.029-0.4740.0760.0900.3160.899
USD-CNY0.5520.4670.6541.0000.259-0.1770.3560.4370.6370.503
USD-EUR0.8240.874-0.0290.2591.0000.7230.3640.7200.685-0.218
USD-GBP0.5270.584-0.474-0.1770.7231.0000.2790.3220.389-0.670
USD-HKD0.3770.3690.0760.3560.3640.2791.0000.4580.328-0.078
USD-JPY0.7020.6760.0900.4370.7200.3220.4581.0000.622-0.008
USD-NZD0.9260.8020.3160.6370.6850.3890.3280.6221.0000.107
USD-XAU-0.004-0.0330.8990.503-0.218-0.670-0.078-0.0080.1071.000

Missing values

2025-04-21T19:56:19.414783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-21T19:56:19.586114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
DATE
2002-02-011.9696671.58911.71938.27661.1636030.7088187.7993134.682.4026910.00353
2002-03-011.9301291.60161.69668.27651.1502190.7061157.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.7025937.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.7063647.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.7080157.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.7072147.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.7033347.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.6979837.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.6999377.7994133.362.3713540.00337
2002-03-011.9301291.60161.69668.27651.1502190.6988127.7994133.362.3713540.00337
USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
DATE
2025-05-011.5681351.38490.81697.29970.8775780.7800317.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7710107.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7538077.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7581507.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7558017.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7550597.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7527857.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7688177.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7641177.7625142.181.6840690.000301
2025-05-011.5681351.38490.81697.29970.8775780.7738147.7625142.181.6840690.000301

Duplicate rows

Most frequently occurring

USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU# duplicates
60.9789531.03060.93676.22180.7658730.6595007.755192.561.2125620.0006323
00.9096700.95520.78556.44150.6945410.6123327.794176.761.1372680.0006152
10.9317930.98990.90446.29380.7504690.6321917.756481.151.1988970.0005902
20.9326620.96340.84046.46340.6895600.6108367.781880.561.2059820.0006662
30.9326620.96340.84046.46340.6895600.6175137.781880.561.2059820.0006662
40.9724791.01740.91326.37930.7437160.6269997.767677.621.2812300.0005732
50.9789531.03060.93676.22180.7658730.6386107.755192.561.2125620.0006322
70.9795281.02130.93816.29490.7715450.6381217.767476.911.2866700.0006392
80.9817400.97160.92896.57700.7243230.6197327.788081.781.3290800.0007092
91.0167771.01940.98246.67400.7170000.6293277.750880.401.3046310.0007362